/***********************************************************************/
/*                                                                     */
/*   svm_learn.h                                                       */
/*                                                                     */
/*   Declarations for learning module of Support Vector Machine.       */
/*                                                                     */
/*   Author: Thorsten Joachims                                         */
/*   Date: 02.07.02                                                    */
/*                                                                     */
/*   Copyright (c) 2002  Thorsten Joachims - All rights reserved       */
/*                                                                     */
/*   This software is available for non-commercial use only. It must   */
/*   not be modified and distributed without prior permission of the   */
/*   author. The author is not responsible for implications from the   */
/*   use of this software.                                             */
/*                                                                     */
/***********************************************************************/

#ifndef SVM_LEARN
#define SVM_LEARN

void   svm_learn_classification(DOC **, double *, long, long, LEARN_PARM *,
                                KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
                                double *);
void   svm_learn_regression(DOC **, double *, long, long, LEARN_PARM *,
                            KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
void   svm_learn_ranking(DOC **, double *, long, long, LEARN_PARM *,
                         KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
void   svm_learn_optimization(DOC **, double *, long, long, LEARN_PARM *,
                              KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
                              double *);
long   optimize_to_convergence(DOC **, long *, long, long, LEARN_PARM *,
                               KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
                               MODEL *, long *, long *, double *,
                               double *, double *,
                               TIMING *, double *, long, long);
long   optimize_to_convergence_sharedslack(DOC **, long *, long, long,
        LEARN_PARM *,
        KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
        MODEL *, double *, double *, double *,
        TIMING *, double *);
double compute_objective_function(double *, double *, double *, double,
                                  long *, long *);
void   clear_index(long *);
void   add_to_index(long *, long);
long   compute_index(long *,long, long *);
void   optimize_svm(DOC **, long *, long *, long *, double, long *, long *,
                    MODEL *,
                    long, long *, long, double *, double *, double *,
                    LEARN_PARM *, CFLOAT *, KERNEL_PARM *, QP *, double *);
void   compute_matrices_for_optimization(DOC **, long *, long *, long *, double,
        long *,
        long *, long *, MODEL *, double *,
        double *, double *, long, long, LEARN_PARM *,
        CFLOAT *, KERNEL_PARM *, QP *);
long   calculate_svm_model(DOC **, long *, long *, double *, double *,
                           double *, double *, LEARN_PARM *, long *,
                           long *, MODEL *);
long   check_optimality(MODEL *, long *, long *, double *, double *,
                        double *, long,
                        LEARN_PARM *,double *, double, long *, long *, long *,
                        long *, long, KERNEL_PARM *);
long   check_optimality_sharedslack(DOC **docs, MODEL *model, long int *label,
                                    double *a, double *lin, double *c, double *slack,
                                    double *alphaslack, long int totdoc,
                                    LEARN_PARM *learn_parm, double *maxdiff,
                                    double epsilon_crit_org, long int *misclassified,
                                    long int *active2dnum,
                                    long int *last_suboptimal_at,
                                    long int iteration, KERNEL_PARM *kernel_parm);
void   compute_shared_slacks(DOC **docs, long int *label, double *a,
                             double *lin, double *c, long int *active2dnum,
                             LEARN_PARM *learn_parm,
                             double *slack, double *alphaslack);
long   identify_inconsistent(double *, long *, long *, long, LEARN_PARM *,
                             long *, long *);
long   identify_misclassified(double *, long *, long *, long,
                              MODEL *, long *, long *);
long   identify_one_misclassified(double *, long *, long *, long,
                                  MODEL *, long *, long *);
long   incorporate_unlabeled_examples(MODEL *, long *,long *, long *,
                                      double *, double *, long, double *,
                                      long *, long *, long, KERNEL_PARM *,
                                      LEARN_PARM *);
void   update_linear_component(DOC **, long *, long *, double *, double *,
                               long *, long, long, KERNEL_PARM *,
                               KERNEL_CACHE *, double *,
                               CFLOAT *, double *);
long   select_next_qp_subproblem_grad(long *, long *, double *,
                                      double *, double *, long,
                                      long, LEARN_PARM *, long *, long *,
                                      long *, double *, long *, KERNEL_CACHE *,
                                      long, long *, long *);
long   select_next_qp_subproblem_rand(long *, long *, double *,
                                      double *, double *, long,
                                      long, LEARN_PARM *, long *, long *,
                                      long *, double *, long *, KERNEL_CACHE *,
                                      long *, long *, long);
long   select_next_qp_slackset(DOC **docs, long int *label, double *a,
                               double *lin, double *slack, double *alphaslack,
                               double *c, LEARN_PARM *learn_parm,
                               long int *active2dnum, double *maxviol);
void   select_top_n(double *, long, long *, long);
void   init_shrink_state(SHRINK_STATE *, long, long);
void   shrink_state_cleanup(SHRINK_STATE *);
long   shrink_problem(DOC **, LEARN_PARM *, SHRINK_STATE *, KERNEL_PARM *,
                      long *, long *, long, long, long, double *, long *);
void   reactivate_inactive_examples(long *, long *, double *, SHRINK_STATE *,
                                    double *, double*, long, long, long, LEARN_PARM *,
                                    long *, DOC **, KERNEL_PARM *,
                                    KERNEL_CACHE *, MODEL *, CFLOAT *,
                                    double *, double *);

/* cache kernel evalutations to improve speed */
KERNEL_CACHE *kernel_cache_init(long, long);
void   kernel_cache_cleanup(KERNEL_CACHE *);
void   get_kernel_row(KERNEL_CACHE *,DOC **, long, long, long *, CFLOAT *,
                      KERNEL_PARM *);
void   cache_kernel_row(KERNEL_CACHE *,DOC **, long, KERNEL_PARM *);
void   cache_multiple_kernel_rows(KERNEL_CACHE *,DOC **, long *, long,
                                  KERNEL_PARM *);
void   kernel_cache_shrink(KERNEL_CACHE *,long, long, long *);
void   kernel_cache_reset_lru(KERNEL_CACHE *);
long   kernel_cache_malloc(KERNEL_CACHE *);
void   kernel_cache_free(KERNEL_CACHE *,long);
long   kernel_cache_free_lru(KERNEL_CACHE *);
CFLOAT *kernel_cache_clean_and_malloc(KERNEL_CACHE *,long);
long   kernel_cache_touch(KERNEL_CACHE *,long);
long   kernel_cache_check(KERNEL_CACHE *,long);
long   kernel_cache_space_available(KERNEL_CACHE *);

void compute_xa_estimates(MODEL *, long *, long *, long, DOC **,
                          double *, double *, KERNEL_PARM *,
                          LEARN_PARM *, double *, double *, double *);
double xa_estimate_error(MODEL *, long *, long *, long, DOC **,
                         double *, double *, KERNEL_PARM *,
                         LEARN_PARM *);
double xa_estimate_recall(MODEL *, long *, long *, long, DOC **,
                          double *, double *, KERNEL_PARM *,
                          LEARN_PARM *);
double xa_estimate_precision(MODEL *, long *, long *, long, DOC **,
                             double *, double *, KERNEL_PARM *,
                             LEARN_PARM *);
void avg_similarity_of_sv_of_one_class(MODEL *, DOC **, double *, long *, KERNEL_PARM *, double *, double *);
double most_similar_sv_of_same_class(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *);
double distribute_alpha_t_greedily(long *, long, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
double distribute_alpha_t_greedily_noindex(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
void estimate_transduction_quality(MODEL *, long *, long *, long, DOC **, double *);
double estimate_margin_vcdim(MODEL *, double, double, KERNEL_PARM *);
double estimate_sphere(MODEL *, KERNEL_PARM *);
double estimate_r_delta_average(DOC **, long, KERNEL_PARM *);
double estimate_r_delta(DOC **, long, KERNEL_PARM *);
double length_of_longest_document_vector(DOC **, long, KERNEL_PARM *);

void   write_model(char *, MODEL *);
void   write_prediction(char *, MODEL *, double *, double *, long *, long *,
                        long, LEARN_PARM *);
void   write_alphas(char *, double *, long *, long);

typedef struct cache_parm_s {
    KERNEL_CACHE *kernel_cache;
    CFLOAT *cache;
    DOC **docs;
    long m;
    KERNEL_PARM *kernel_parm;
    long offset,stepsize;
} cache_parm_t;

#endif
